ABSTRACT One of the aims of SOA is to compose atomic web services into a powerful composite service. QoS based selection approaches are used to choose the best solution among candidate services with the same functionality. Due to the increasing scale of the candidate services and demands for real-time in some specific application domains, the rapid convergent algorithm for large-scale web service composition is especially important, but rare work has been done to solve the problem. This paper describes the Web services composition model and constructs the web service selection mathematical model. According to these models, service composition problem can be considered as Single-Objective Multi-Constraints optimization problem. We propose a new algorithm named GAELS (Genetic Algorithm Embedded Local Searching), which uses the strategies of enhanced initial population and mutation with local searching, to speed up the convergence. Finally, the in-depth experimental results show that the GAELS algorithm can get the non-inferior solution more quickly and more adaptively than simple genetic algorithm in large-scale web service composition.